1. Field of the Invention
The present invention relates to an image processing method and apparatus, and more particularly, to an image processing method capable of effectively removing noise contained in an image photographed in a low light environment by using statistical information, and a system thereof.
2. Description of the Related Art
Today, owing to the development of video technology, video multimedia is being developed in which high performance cameras, digital cameras, closed-circuit televisions (CCTVs), video capture systems, and the like can take a picture and store various images.
However, in the case an image compressed from various formats as above or a transmitted image is photographed in a low light environment, noise contained in the image may deteriorate its quality and also decrease its ability to be compressed effectively.
Noise that matters in a low light environment includes Poisson and photon counting noise and false color noise.
FIG. 1 is a view illustrating a configuration of noise contained in an image photographed with a video camera. Referring to FIG. 1, in an image photographed with a conventional video camera, Poisson and photon counting noise 101 and false color noise 102 takes large portion of the entire noise.
Poisson and photon counting noise and false color noise is noise associated with the inconsecutive properties of an image capturing device, when an image is photographed in a low light environment. The distribution thereof is normal or similar to Gaussian distribution.
False color noise is noise distributed in all color factors, deteriorates the quality of an image, and introduces a large error in motion compensation of most video coding algorithms. FIG. 2 is a view illustrating an example of false color noise. Referring to FIG. 2, false color noise is distributed in almost all color factors.
A pixel that has been affected by false color noise may contribute to a deteriorated compression ratio. Thus, it is important to remove the false color noise in an image before compressing the image.
A method of simultaneously using a spatial filter and a temporal filter has been suggested to remove the noise described above. The filter as above is a spatio-temporal filter.
However, a conventional spatio-temporal filtering method removes only one type of noise from a plurality of noises. Also, smearing occurs in an area without noise, which deteriorates the quality of an image.
Also, unlike impulsive noise, Poisson and photon counting noise contains both uncorrelated and correlated noise occurring in the same region. However, the conventional filtering method determined Poisson and photon counting noise inaccurately. Also, the filtering method itself was ineffective.